Causal Cortical and Thalamic Connections in the Human Brain.

The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.

Rates and Predictors of Pain Reduction With Intracranial Stimulation for Intractable Pain Disorders.

BACKGROUND AND OBJECTIVES: Intracranial modulation paradigms, namely deep brain stimulation (DBS) and motor cortex stimulation (MCS), have been used to treat intractable pain disorders. However, treatment efficacy remains heterogeneous, and factors associated with pain reduction are not completely understood. METHODS: We performed an individual patient review of pain outcomes (visual analog scale, quality-of-life measures, complications, pulse generator implant rate, cessation of stimulation) after implantation of DBS or MCS devices. We evaluated 663 patients from 36 study groups and stratified outcomes by pain etiology and implantation targets. RESULTS: Included studies comprised primarily retrospective cohort studies. MCS patients had a similar externalized trial success rate compared with DBS patients (86% vs 81%; P = .16), whereas patients with peripheral pain had a higher trial success rate compared with patients with central pain (88% vs 79%; P = .004). Complication rates were similar for MCS and DBS patients (12% vs 15%; P = .79). Patients with peripheral pain had lower likelihood of device cessation compared with those with central pain (5.7% vs 10%; P = .03). Of all implanted patients, mean pain reduction at last follow-up was 45.8% (95% CI: 40.3-51.2) with a 31.2% (95% CI: 12.4-50.1) improvement in quality of life. No difference was seen between MCS patients (43.8%; 95% CI: 36.7-58.2) and DBS patients (48.6%; 95% CI: 39.2-58) or central (41.5%; 95% CI: 34.8-48.2) and peripheral (46.7%; 95% CI: 38.9-54.5) etiologies. Multivariate analysis identified the anterior cingulate cortex target to be associated with worse pain reduction, while postherpetic neuralgia was a positive prognostic factor. CONCLUSION: Both DBS and MCS have similar efficacy and complication rates in the treatment of intractable pain. Patients with central pain disorders tended to have lower trial success and higher rates of device cessation. Additional prognostic factors include anterior cingulate cortex targeting and postherpetic neuralgia diagnosis. These findings underscore intracranial neurostimulation as an important modality for treatment of intractable pain disorders.

Causal Cortical and Thalamic Connections in the Human Brain.

The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.

Naturalistic acute pain states decoded from neural and facial dynamics.

Pain is a complex experience that remains largely unexplored in naturalistic contexts, hindering our understanding of its neurobehavioral representation in ecologically valid settings. To address this, we employed a multimodal, data-driven approach integrating intracranial electroencephalography, pain self-reports, and facial expression quantification to characterize the neural and behavioral correlates of naturalistic acute pain in twelve epilepsy patients undergoing continuous monitoring with neural and audiovisual recordings. High self-reported pain states were associated with elevated blood pressure, increased pain medication use, and distinct facial muscle activations. Using machine learning, we successfully decoded individual participants' high versus low self-reported pain states from distributed neural activity patterns (mean AUC = 0.70), involving mesolimbic regions, striatum, and temporoparietal cortex. High self-reported pain states exhibited increased low-frequency activity in temporoparietal areas and decreased high-frequency activity in mesolimbic regions (hippocampus, cingulate, and orbitofrontal cortex) compared to low pain states. This neural pain representation remained stable for hours and was modulated by pain onset and relief. Objective facial expression changes also classified self-reported pain states, with results concordant with electrophysiological predictions. Importantly, we identified transient periods of momentary pain as a distinct naturalistic acute pain measure, which could be reliably differentiated from affect-neutral periods using intracranial and facial features, albeit with neural and facial patterns distinct from self-reported pain. These findings reveal reliable neurobehavioral markers of naturalistic acute pain across contexts and timescales, underscoring the potential for developing personalized pain interventions in real-world settings.

Dichotomous frequency-dependent phase synchrony in the sensorimotor network characterizes simplistic movement.

It is hypothesized that disparate brain regions interact via synchronous activity to control behavior. The nature of these interconnected ensembles remains an area of active investigation, and particularly the role of high frequency synchronous activity in simplistic behavior is not well known. Using intracranial electroencephalography, we explored the spectral dynamics and network connectivity of sensorimotor cortical activity during a simple motor task in seven epilepsy patients. Confirming prior work, we see a "spectral tilt" (increased high-frequency (HF, 70-100 Hz) and decreased low-frequency (LF, 3-33 Hz) broadband oscillatory activity) in motor regions during movement compared to rest, as well as an increase in LF synchrony between these regions using time-resolved phase-locking. We then explored this phenomenon in high frequency and found a robust but opposite effect, where time-resolved HF broadband phase-locking significantly decreased during movement. This "connectivity tilt" (increased LF synchrony and decreased HF synchrony) displayed a graded anatomical dependency, with the most robust pattern occurring in primary sensorimotor cortical interactions and less robust pattern occurring in associative cortical interactions. Connectivity in theta (3-7 Hz) and high beta (23-27 Hz) range had the most prominent low frequency contribution during movement, with theta synchrony building gradually while high beta having the most prominent effect immediately following the cue. There was a relatively sharp, opposite transition point in both the spectral and connectivity tilt at approximately 35 Hz. These findings support the hypothesis that task-relevant high-frequency spectral activity is stochastic and that the decrease in high-frequency synchrony may facilitate enhanced low frequency phase coupling and interregional communication. Thus, the "connectivity tilt" may characterize behaviorally meaningful cortical interactions.

Dosimetric Comparison of Dedicated Radiosurgery Platforms for the Treatment of Essential Tremor: Technical Report.

Essential tremor (ET) is one of the most common adult movement disorders. As the worldwide population ages, the incidence and prevalence of ET is increasing. Although most cases can be managed conservatively, there is a subset of ET that is refractory to medical management. By virtue of being "reversible", deep brain stimulation (DBS) of the ventral intermediate nucleus (VIM) of the thalamus is one commonly accepted intervention. As an alternative to invasive and expensive DBS, there has been a renaissance in treating ET with lesion-based approaches, spearheaded most recently by high-intensity focused ultrasound (HIFU), the hallmark of which is that it is non-invasive. Meanwhile, stereotactic radiosurgical (SRS) lesioning of VIM represents another time-honored lesion-based non-invasive treatment of ET, which is especially well suited for those patients that cannot tolerate open neurosurgery and is now also getting a "second look". While multiple SRS platforms have been and continue to be used to treat ET, there is little in the way of dosimetric comparison between different technologies. In this brief technical report we compare the dosimetric profiles of three major radiosurgical platforms (Gamma Knife, CyberKnife Robotic Radiosurgery, and Zap-X Gyroscopic Radiosurgery (GRS)) for the treatment of ET. In general, the GRS and Gamma Knife were shown to have the best theoretical dosimetric profiles for VIM lesioning. Nevertheless the relevance of such superiority to clinical outcomes requires future patient studies.

Emerging Outlook on Personalized Neuromodulation for Depression: Insights From Tractography-Based Targeting.

BACKGROUND: Deep brain stimulation has shown promise in treating individual patients with treatment-resistant depression, but larger-scale trials have been less successful. Here, we created what is, to our knowledge, the largest meta-analysis with individual patient data to date to explore whether the use of tractography enhances the efficacy of deep brain stimulation for treatment-resistant depression. METHODS: We systematically reviewed 1823 articles, selecting 32 that contributed data from 366 patients. We stratified the individual patient data based on stimulation target and use of tractography. Using 2-way type III analysis of variance, Welch's 2-sample t tests, and mixed-effects linear regression models, we evaluated changes in depression severity 1 year (9-15 months) postoperatively and at last follow-up (4 weeks to 8 years) as assessed by depression scales. RESULTS: Tractography was used for medial forebrain bundle (MFB) (n = 17 tractography/32 total), subcallosal cingulate (SCC) (n = 39 tractography/241 total), and ventral capsule/ventral striatum (n = 3 tractography/41 total) targets; it was not used for bed nucleus of stria terminalis (n = 11), lateral habenula (n = 10), and inferior thalamic peduncle (n = 1). Across all patients, tractography significantly improved mean depression scores at 1 year (p < .001) and last follow-up (p = .009). Within the target cohorts, tractography improved depression scores at 1 year for both MFB and SCC, though significance was met only at the α = 0.1 level (SCC: ß = 15.8%, p = .09; MFB: ß = 52.4%, p = .10). Within the tractography cohort, patients with MFB tractography showed greater improvement than patients with SCC tractography (72.42 ± 7.17% vs. 54.78 ± 4.08%) at 1 year (p = .044). CONCLUSIONS: Our findings underscore the promise of tractography in deep brain stimulation for treatment-resistant depression as a method for personalization of therapy, supporting its inclusion in future trials.

The fasciola cinereum of the hippocampal tail as an interventional target in epilepsy.

Targeted tissue ablation involving the anterior hippocampus is the standard of care for patients with drug-resistant mesial temporal lobe epilepsy. However, a substantial proportion continues to suffer from seizures even after surgery. We identified the fasciola cinereum (FC) neurons of the posterior hippocampal tail as an important seizure node in both mice and humans with epilepsy. Genetically defined FC neurons were highly active during spontaneous seizures in epileptic mice, and closed-loop optogenetic inhibition of these neurons potently reduced seizure duration. Furthermore, we specifically targeted and found the prominent involvement of FC during seizures in a cohort of six patients with epilepsy. In particular, targeted lesioning of the FC in a patient reduced the seizure burden present after ablation of anterior mesial temporal structures. Thus, the FC may be a promising interventional target in epilepsy.

Ultrasound-Induced Cascade Amplification in a Mechanoluminescent Nanotransducer for Enhanced Sono-Optogenetic Deep Brain Stimulation.

Remote and genetically targeted neuromodulation in the deep brain is important for understanding and treatment of neurological diseases. Ultrasound-triggered mechanoluminescent technology offers a promising approach for achieving remote and genetically targeted brain modulation. However, its application has thus far been limited to shallow brain depths due to challenges related to low sonochemical reaction efficiency and restricted photon yields. Here we report a cascaded mechanoluminescent nanotransducer to achieve efficient light emission upon ultrasound stimulation. As a result, blue light was generated under ultrasound stimulation with a subsecond response latency. Leveraging the high energy transfer efficiency of focused ultrasound in brain tissue and the high sensitivity to ultrasound of these mechanoluminescent nanotransducers, we are able to show efficient photon delivery and activation of ChR2-expressing neurons in both the superficial motor cortex and deep ventral tegmental area after intracranial injection. Our liposome nanotransducers enable minimally invasive deep brain stimulation for behavioral control in animals via a flexible, mechanoluminescent sono-optogenetic system.

Developing the surgeon-machine interface: using a novel instance-segmentation framework for intraoperative landmark labelling.

Introduction: The utilisation of artificial intelligence (AI) augments intraoperative safety, surgical training, and patient outcomes. We introduce the term Surgeon-Machine Interface (SMI) to describe this innovative intersection between surgeons and machine inference. A custom deep computer vision (CV) architecture within a sparse labelling paradigm was developed, specifically tailored to conceptualise the SMI. This platform demonstrates the ability to perform instance segmentation on anatomical landmarks and tools from a single open spinal dural arteriovenous fistula (dAVF) surgery video dataset. Methods: Our custom deep convolutional neural network was based on SOLOv2 architecture for precise, instance-level segmentation of surgical video data. Test video consisted of 8520 frames, with sparse labelling of only 133 frames annotated for training. Accuracy and inference time, assessed using F1-score and mean Average Precision (mAP), were compared against current state-of-the-art architectures on a separate test set of 85 additionally annotated frames. Results: Our SMI demonstrated superior accuracy and computing speed compared to these frameworks. The F1-score and mAP achieved by our platform were 17% and 15.2% respectively, surpassing MaskRCNN (15.2%, 13.9%), YOLOv3 (5.4%, 11.9%), and SOLOv2 (3.1%, 10.4%). Considering detections that exceeded the Intersection over Union threshold of 50%, our platform achieved an impressive F1-score of 44.2% and mAP of 46.3%, outperforming MaskRCNN (41.3%, 43.5%), YOLOv3 (15%, 34.1%), and SOLOv2 (9%, 32.3%). Our platform demonstrated the fastest inference time (88ms), compared to MaskRCNN (90ms), SOLOV2 (100ms), and YOLOv3 (106ms). Finally, the minimal amount of training set demonstrated a good generalisation performance -our architecture successfully identified objects in a frame that were not included in the training or validation frames, indicating its ability to handle out-of-domain scenarios. Discussion: We present our development of an innovative intraoperative SMI to demonstrate the future promise of advanced CV in the surgical domain. Through successful implementation in a microscopic dAVF surgery, our framework demonstrates superior performance over current state-of-the-art segmentation architectures in intraoperative landmark guidance with high sample efficiency, representing the most advanced AI-enabled surgical inference platform to date. Our future goals include transfer learning paradigms for scaling to additional surgery types, addressing clinical and technical limitations for performing real-time decoding, and ultimate enablement of a real-time neurosurgical guidance platform.

Subjective states induced by intracranial electrical stimulation matches the cytoarchitectonic organization of the human insula.

Functions of the human insula have been explored extensively with neuroimaging methods and intracranial electrical stimulation studies that have highlighted a functional segregation across its subregions. A recently developed cytoarchitectonic map of the human insula has also segregated this brain region into various areas. Our knowledge of the functional organization of this brain region at the level of these fine-parceled microstructural areas remains only partially understood. We address this gap of knowledge by applying a multimodal approach linking direct electrical stimulation and task-evoked intracranial EEG recordings with microstructural subdivisions of the human insular cortex. In 17 neurosurgical patients with 142 implanted electrodes, stimulation of 40 % of the sites induced a reportable change in the conscious experience of the subjects in visceral/autonomic, anxiety, taste/olfactory, pain/temperature as well as somatosensory domains. These subjective responses showed a topographical allocation to microstructural areas defined by probabilistic cytoarchitectonic parcellation maps of the human insula. We found the pain and thermal responses to be located in areas lg2/ld2, while non-painful/non-thermal somatosensory responses corresponded to area ld3 and visceroceptive responses to area Id6. Lastly, the stimulation of area Id7 in the dorsal anterior insula, failed to induce reportable changes to subjective experience even though intracranial EEG recordings from this region captured significant time-locked high-frequency activity (HFA). Our results provide a multimodal map of functional subdivisions within the human insular cortex at the individual brain basis and characterize their anatomical association with fine-grained cytoarchitectonic parcellations of this brain structure.

Accumbens connectivity during deep-brain stimulation differentiates loss of control from physiologic behavioral states.

BACKGROUND: Loss of control (LOC) eating, the subjective sense that one cannot control what or how much one eats, characterizes binge-eating behaviors pervasive in obesity and related eating disorders. Closed-loop deep-brain stimulation (DBS) for binge eating should predict LOC and trigger an appropriately timed intervention. OBJECTIVE/HYPOTHESIS: This study aimed to identify a sensitive and specific biomarker to detect LOC onset for DBS. We hypothesized that changes in phase-locking value (PLV) predict the onset of LOC-associated cravings and distinguish them from potential confounding states. METHODS: Using DBS data recorded from the nucleus accumbens (NAc) of two patients with binge eating disorder (BED) and severe obesity, we compared PLV between inter- and intra-hemispheric NAc subregions for three behavioral conditions: craving (associated with LOC eating), hunger (not associated with LOC), and sleep. RESULTS: In both patients, PLV in the high gamma frequency band was significantly higher for craving compared to sleep and significantly higher for hunger compared to craving. Maximum likelihood classifiers achieved accuracies above 88% when differentiating between the three conditions. CONCLUSIONS: High-frequency inter- and intra-hemispheric PLV in the NAc is a promising biomarker for closed-loop DBS that differentiates LOC-associated cravings from physiologic states such as hunger and sleep. Future trials should assess PLV as a LOC biomarker across a larger cohort and a wider patient population transdiagnostically.

An Individualized Tractography Pipeline for the Nucleus Basalis of Meynert Lateral Tract.

Background: At the center of the cortical cholinergic network, the nucleus basalis of Meynert (NBM) is crucial for the cognitive domains most vulnerable in PD. Preclinical evidence has demonstrated the positive impact of NBM deep brain stimulation (DBS) on cognition but early human trials have had mixed results. It is possible that DBS of the lateral NBM efferent white matter fiber bundle may be more effective at improving cognitive-motor function. However, precise tractography modelling is required to identify the optimal target for neurosurgical planning. Individualized tractography approaches have been shown to be highly effective for accurately identifying DBS targets but have yet to be developed for the NBM. Methods: Using structural and diffusion weighted imaging, we developed a tractography pipeline for precise individualized identification of the lateral NBM target tract. Using dice similarity coefficients, the reliability of the tractography outputs was assessed across three cohorts to investigate: 1) whether this manual pipeline is more reliable than an existing automated pipeline currently used in the literature; 2) the inter- and intra-rater reliability of our pipeline in research scans of patients with PD; and 3) the reliability and practicality of this pipeline in clinical scans of DBS patients. Results: The individualized manual pipeline was found to be significantly more reliable than the existing automated pipeline for both the segmentation of the NBM region itself (p<0.001) and the reconstruction of the target lateral tract (p=0.002). There was also no significant difference between the reliability of two different raters in the PD cohort (p=0.25), which showed high inter- (mean Dice coefficient >0.6) and intra-rater (mean Dice coefficient >0.7) reliability across runs. Finally, the pipeline was shown to be highly reliable within the clinical scans (mean Dice coefficient = 0.77). However, accurate reconstruction was only evident in 7/10 tracts. Conclusion: We have developed a reliable tractography pipeline for the identification and analysis of the NBM lateral tract in research and clinical grade imaging of healthy young adult and PD patient scans.

Long-term outcomes of mesial temporal laser interstitial thermal therapy for drug-resistant epilepsy and subsequent surgery for seizure recurrence: a multi-centre cohort study.

BACKGROUND: Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive alternative to surgical resection for drug-resistant mesial temporal lobe epilepsy (mTLE). Reported rates of seizure freedom are variable and long-term durability is largely unproven. Anterior temporal lobectomy (ATL) remains an option for patients with MRgLITT treatment failure. However, the safety and efficacy of this staged strategy is unknown. METHODS: This multicentre, retrospective cohort study included 268 patients consecutively treated with mesial temporal MRgLITT at 11 centres between 2012 and 2018. Seizure outcomes and complications of MRgLITT and any subsequent surgery are reported. Predictive value of preoperative variables for seizure outcome was assessed. RESULTS: Engel I seizure freedom was achieved in 55.8% (149/267) at 1 year, 52.5% (126/240) at 2 years and 49.3% (132/268) at the last follow-up ≥1 year (median 47 months). Engel I or II outcomes were achieved in 74.2% (198/267) at 1 year, 75.0% (180/240) at 2 years and 66.0% (177/268) at the last follow-up. Preoperative focal to bilateral tonic-clonic seizures were independently associated with seizure recurrence. Among patients with seizure recurrence, 14/21 (66.7%) became seizure-free after subsequent ATL and 5/10 (50%) after repeat MRgLITT at last follow-up≥1 year. CONCLUSIONS: MRgLITT is a viable treatment with durable outcomes for patients with drug-resistant mTLE evaluated at a comprehensive epilepsy centre. Although seizure freedom rates were lower than reported with ATL, this series represents the early experience of each centre and a heterogeneous cohort. ATL remains a safe and effective treatment for well-selected patients who fail MRgLITT.

Causal evidence for the processing of bodily self in the anterior precuneus.

To probe the causal importance of the human posteromedial cortex (PMC) in processing the sense of self, we studied a rare cohort of nine patients with electrodes implanted bilaterally in the precuneus, posterior cingulate, and retrosplenial regions with a combination of neuroimaging, intracranial recordings, and direct cortical stimulations. In all participants, the stimulation of specific sites within the anterior precuneus (aPCu) caused dissociative changes in physical and spatial domains. Using single-pulse electrical stimulations and neuroimaging, we present effective and resting-state connectivity of aPCu hot zone with the rest of the brain and show that they are located outside the boundaries of the default mode network (DMN) but connected reciprocally with it. We propose that the function of this subregion of the PMC is integral to a range of cognitive processes that require the self's physical point of reference, given its location within a spatial environment.

Multisite thalamic recordings to characterize seizure propagation in the human brain.

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in a subset of patients with refractory focal epilepsy. One important uncertainty is to what extent thalamic subregions other than the ANT could be recruited more prominently in the propagation of focal onset seizures. We designed the current study to simultaneously monitor the engagement of the ANT, mediodorsal (MD) and pulvinar (PUL) nuclei during seizures in patients who could be candidates for thalamic neuromodulation. We studied 11 patients with clinical manifestations of presumed temporal lobe epilepsy (TLE) undergoing invasive stereo-encephalography (sEEG) monitoring to confirm the source of their seizures. We extended cortical electrodes to reach the ANT, MD and PUL nuclei of the thalamus. More than one thalamic subdivision was simultaneously interrogated in nine patients. We recorded seizures with implanted electrodes across various regions of the brain and documented seizure onset zones (SOZ) in each recorded seizure. We visually identified the first thalamic subregion to be involved in seizure propagation. Additionally, in eight patients, we applied repeated single pulse electrical stimulation in each SOZ and recorded the time and prominence of evoked responses across the implanted thalamic regions. Our approach for multisite thalamic sampling was safe and caused no adverse events. Intracranial EEG recordings confirmed SOZ in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites, highlighting the importance of invasive monitoring for accurate localization of SOZs. In all patients, seizures with the same propagation network and originating from the same SOZ involved the same thalamic subregion, with a stereotyped thalamic EEG signature. Qualitative visual reviews of ictal EEGs were largely consistent with the quantitative analysis of the corticothalamic evoked potentials, and both documented that thalamic nuclei other than ANT could have the earliest participation in seizure propagation. Specifically, pulvinar nuclei were involved earlier and more prominently than ANT in more than half of the patients. However, which specific thalamic subregion first demonstrated ictal activity could not be reliably predicted based on clinical semiology or lobar localization of SOZs. Our findings document the feasibility and safety of bilateral multisite sampling from the human thalamus. This may allow more personalized thalamic targets to be identified for neuromodulation. Future studies are needed to determine if a personalized thalamic neuromodulation leads to greater improvements in clinical outcome.

Taking modern psychiatry into the metaverse: Integrating augmented, virtual, and mixed reality technologies into psychiatric care.

The landscape of psychiatry is ever evolving and has recently begun to be influenced more heavily by new technologies. One novel technology which may have particular application to psychiatry is the metaverse, a three-dimensional digital social platform accessed via augmented, virtual, and mixed reality (AR/VR/MR). The metaverse allows the interaction of users in a virtual world which can be measured and manipulated, posing at once exciting new possibilities and significant potential challenges and risks. While the final form of the nascent metaverse is not yet clear, the immersive simulation and holographic mixed reality-based worlds made possible by the metaverse have the potential to redefine neuropsychiatric care for both patients and their providers. While a number of applications for this technology can be envisioned, this article will focus on leveraging the metaverse in three specific domains: medical education, brain stimulation, and biofeedback. Within medical education, the metaverse could allow for more precise feedback to students performing patient interviews as well as the ability to more easily disseminate highly specialized technical skills, such as those used in advanced neurostimulation paradigms. Examples of potential applications in brain stimulation and biofeedback range from using AR to improve precision targeting of non-invasive neuromodulation modalities to more innovative practices, such as using physiological and behavioral measures derived from interactions in VR environments to directly inform and personalize treatment parameters for patients. Along with promising future applications, we also discuss ethical implications and data security concerns that arise when considering the introduction of the metaverse and related AR/VR technologies to psychiatric research and care.

Methods and Impact for Using Federated Learning to Collaborate on Clinical Research.

BACKGROUND: The development of accurate machine learning algorithms requires sufficient quantities of diverse data. This poses a challenge in health care because of the sensitive and siloed nature of biomedical information. Decentralized algorithms through federated learning (FL) avoid data aggregation by instead distributing algorithms to the data before centrally updating one global model. OBJECTIVE: To establish a multicenter collaboration and assess the feasibility of using FL to train machine learning models for intracranial hemorrhage (ICH) detection without sharing data between sites. METHODS: Five neurosurgery departments across the United States collaborated to establish a federated network and train a convolutional neural network to detect ICH on computed tomography scans. The global FL model was benchmarked against a standard, centrally trained model using a held-out data set and was compared against locally trained models using site data. RESULTS: A federated network of practicing neurosurgeon scientists was successfully initiated to train a model for predicting ICH. The FL model achieved an area under the ROC curve of 0.9487 (95% CI 0.9471-0.9503) when predicting all subtypes of ICH compared with a benchmark (non-FL) area under the ROC curve of 0.9753 (95% CI 0.9742-0.9764), although performance varied by subtype. The FL model consistently achieved top three performance when validated on any site's data, suggesting improved generalizability. A qualitative survey described the experience of participants in the federated network. CONCLUSION: This study demonstrates the feasibility of implementing a federated network for multi-institutional collaboration among clinicians and using FL to conduct machine learning research, thereby opening a new paradigm for neurosurgical collaboration.

Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating.

Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.